zn.rar_DDST_ST_fix5a9_single carrier_zn545

clc; clear; close all; % L - channel order % N - size of the block before adding cyclic-prefix % M - size of the block after adding cyclic-prefix % P - period of the superimposed training vector (has to be equal to L) % c - training vector %****************** %% 单载波传输 传输一个符号 %%**********% %% 参数设置 L=3;%信道路径 M=L+1; %导频周期数 N=40;%载波长度 K=N/M; %导频重复数 SigmaC2 = 0.2;%导频处的功率分配 SigmaS2 = 1 - SigmaC2; %% 生成导频符号 c_P=Fun_Train_Seq_Gen20120501(M,1); %c_P=complex([1:P]./P,-[P:-1:1]./P); c=(SigmaC2.^0.5)*kron(ones(K,1),c_P.'); C=Fun_CirMatrixGen(N,c); Power_c = sum(conj(c).*c)/length(c); %% 信噪比 SNR=0:5:30; SNR_lin=10.^(-SNR./10); N0 = 1./(SNR_lin); % power allocation to training and data (must add to 1) Q_m=2;%数据符号调制类型 %% 仿真开始 for ii=1:length(SNR) % w - data vector t0=randi([0 1],N*2,1); w0 = (SigmaS2.^0.5)*Modulator(t0,Q_m); Power_w0 = sum(conj(w0).*w0)/length(w0); J=kron((1/K)*ones(K),eye(M)); x=(eye(N)-J)*w0; % F=dftmtx(N);%%FFT矩阵 % X1 = F*x; % diag_x=diag(X1); % X_hat=F'*diag_x*F./N; % X=Fun_CirMatrixGen(N,x); % s - data + training (at appropriate powers and SNR) s =x + c; %% 信道 h=Fun_Ray_Muti_Exp_DelayPowerProfile20120419(L); h1 = zeros(1,40); h1(1,1:3) = h; F=dftmtx(N);%%FFT矩阵 H1 = F*h1.'; diag_h=diag(H1); HH=F'*diag_h*F./N; H_1 = H1(1:K:end,1); %h=h/(1/L)*sum(sum((abs(h)).^2)); H=toeplitz(h1.',[h(1) zeros(1,N-L) h(end:-1:2)]); %% x - transmitted signal y1=H*s; % y2=S*h1.'; %% 加噪声 % v - random noise y =awgn(y1,SNR(ii)); v=y-y1; noisePower=sum(abs(y-y1).^2)/length(y-y1); %% F - DFT matrix y_hat=F*y./sqrt(N);% x_hat=F*x./sqrt(N); c_hat=F*c./sqrt(N);% Tc=1:K:N;c_hat_t=c_hat(Tc); y_hat_t=y_hat(Tc); x_hat_t=x_hat;x_hat_t(Tc)=[]; C_hat=diag(c_hat_t); C_inv=inv(C_hat); %% estimated channel d_hat=C_inv*y_hat_t;%H-ls=Y/C; %% 计算MSE h1=transpose(h1); A = sum(sum((abs(d_hat-H_1)).^2)); B = sum(sum((abs(H_1)).^2)); MSE(ii) = A./B; % %% 均衡 % bb=1:Q:N; % % Tao_x=generate_Tx(N,P,Q); % % y_Tao=Tao_x*y_hat; % y_hat(bb)=[]; % h2 = zeros(1,70); % h2(1,1:7) = h_hat; % F=dftmtx(N);% % H2 = F*h2.'; % H2(bb)=[]; % diagH=diag(H2); % x_hat=MMSE_equ(y_hat,diagH,Power_w0,noisePower,N,P,Q); % x_time=F'*x_hat; % c0=(eye(N)-J)*c; % z=(eye(N)-J)*y; % z_hat=F*z./sqrt(N); % h2 = zeros(1,70); % h2(1,1:7) = h_hat; % H2 = F*h2.'; % H3=1./H2; % H_2 = H2(1:Q:end,1); % G=diag(H3); % u=F'*G*z_hat./sqrt(N); % r0 = DemodulatorHard(x_time, Q_m); %解调 % r1 = DemodulatorHard(u, Q_m); %解调 % numErrs = sum(sum(abs(r0-t0))); % BER(ii) = numErrs/(N*2); % numErrs1 = sum(sum(abs(r1-t0))); % BER1(ii) = numErrs1/(N*2); end SNRind=1:length(SNR); figure(1), semilogy(SNR(SNRind), MSE(SNRind),'^-b'); xlabel('SNR [dB]') ylabel('MSE') title(sprintf('mse',SNR(ii))) legend('mse') grid on hold on % figure(2), % semilogy(SNR(SNRind),BER1,'^-b',SNR(SNRind), BER(SNRind),'^-r'); % xlabel('SNR [dB]') % ylabel('BER') % title(sprintf('ber',SNR(ii))) % legend('BER') % grid on